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Browsing by Author "Choukulkar, Aditya"

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    Offshore Low-Level Jet properties from offshore lidar measurements in the Gulf of Maine
    Pichugina, Yelena; Banta, Robert; Brewer, Alan; Choukulkar, Aditya; Marquis, Melinda; Hardesty, Michael; Weickmann, Ann; Sandberg, Scott A. (Virginia Tech, 2015-06-11)
    The Low Level Jet (LLJ), an atmospheric flow phenomenon well known as an important source for wind power production in the U.S. Great Plains, is not well characterized or understood in offshore regions considered for wind-farm development, due to a lack of wind measurements having needed precision and vertical resolution at turbine rotor heights. These measurements are also needed to verify whether numerical weather prediction (NWP) forecast models are able to predict offshore LLJ speed, height, direction, and other properties, such as shear. To begin to fill this knowledge gap, in this paper, we have analyzed ship-borne Doppler lidar measurements taken in the Gulf of Maine from 09 July to 12 August 2004. The lidar observing system, NOAA /ESRL's High Resolution Doppler Lidar (HRDL), features high-precision and high-resolution wind measurements and a motion compensation system to provide accurate wind data with a static pointing-angle precision of 0.15°, and dynamic precision < 0.5° despite ship and wave motions (Pichugina et al. 2012, J. Appl. Meteor., 51, 327-349). Fine-resolution wind profiles (15-min time resolution and 15-m vertical resolution) obtained from the water surface up to 1 km, were used to statistically characterize LLJ events, including frequency of occurrence, jet speed maxima, and the height of these maxima. LLJ structure was evident in the lidar-measured wind profiles, often during nighttime and transitional periods, but also during the day on occasion. The LLJ strength for the entire experiment ranged from 5 to 20 m s-1 with a mean value of 9.4 m s-1 and a median value of 8.7 m s-1. A high frequency (about 48%) of jet maxima was observed below 200 m above sea level (ASL) as shown in Figure 1, although for some episodes of strong winds (> 15 m s-1), jet maxima were found at 500-600 m ASL. The existence of LLJs can significantly modify wind profiles, producing vertical wind-shears of 0.03 s-1 or more across the rotor layer. The strong speed and directional shear through the rotor layer during LLJ events, as well as the enhanced winds and turbulence, may all act to increase turbine loads, since the top and bottom tips of the blades would operate in different wind regimes. Additionally, the deviation of LLJ-shape profiles from standardized profiles often leads to significant errors in rotor-layer wind speeds and the calculated wind resource power assessments, such as by using the power-law relation, as will be shown by examples. The shear exponent computed from lidar-measured wind speeds at 10 m and 100 m ASL showed diurnal and other nonsystematic variations ranging from 0.09 to 0.24, with mean value of 0.16. The paper will also present statistics and distributions of wind flow parameters aloft in the turbine rotor layer of the marine boundary layer over a range of heights and under various atmospheric conditions, and show diurnal variations of many flow-related quantities critical to wind energy. It will discuss discrepancies in power estimates using measured hub-height and rotor equivalent winds. Such results cannot be captured by surface measurements or by remote sensing instruments with a coarse vertical resolution of data.
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    Wind Forecast Improvement Project-2, improving model physics in complex terrain – NOAA's Plans for Improving the Rapid Refresh and High Resolution Rapid Refresh Models
    Marquis, Melinda; Olson, Joseph; Kenyon, James; Benjamin, Stan; Wilczak, James; Bianco, Laura; Djalalova, Irina; McCaffrey, Katherine; Pichugina, Yelena; Banta, Robert; Choukulkar, Aditya; Echman, Richard; Clifton, Andrew; Carley, Jacob; Cline, Joel (Virginia Tech, 2015-06-11)
    The Department of Energy is leading a second Wind Forecast Improvement Project (WFIP2), which will aim to improve modeling of complex flow. The National Oceanic and Atmospheric Administration (NOAA) will collaborate with DOE and its national labs, and the team led by Vaisala, which includes academic, utility and renewable energy partners. WFIP2 aims to improve model physics and bridge models that describe multiple scales in complex flow. Observations collected during a 12-18 month field campaign in an area bounded by the Columbia River Gorge and Vansycle Ridge will be used for model verification and assimilation. Scales of physical phenomena of interest range from meso-beta (20-200 km) through the meso-gamma (2-20 km) to the microscale (< 1 km). Physical phenomena of particular interest include frontal passages, gap flows, convective outflows, mountain waves, topographic wakes, and marine pushes. The instrumentation for the field campaign, which will begin in the summer of 2015, includes radar wind profilers, sodars, lidar wind profilers, scanning Doppler lidars, microwave radiometers, sonic anemometers, ceilometers, range gauges, high resolution microbarographs, surface energy budget sensors. Sensors on tall towers and wind turbines will also be used. NOAA's 13-km Rapid Refresh (RAP; spanning North America) and 3-km High-Resolution Rapid Refresh (HRRR; covering the CONUS) will be the primary forecast models for this study. The RAP and HRRR are hourly updating assimilation and model forecast system, capable of assimilating many types of observations, including near-surface and aircraft in-situ observations as well as radar reflectivity and satellite radiances. The RAP produces 18-h forecasts and the HRRR produces 15-h forecasts every hour, both using the Advanced Research version of the Weather Research and Forecast (WRF-ARW) model as the forecast model component. The HRRR uses the RAP for lateral boundary conditions. Within the HRRR, a concurrent 750-m nest will be used to develop scale-aware physical parameterization during WFIP2. Model improvements at all scales will be made available to the public via the WRF-ARW repository. NOAA will assimilate special WFIP2 observations, using them to verify the operational RAP and HRRR forecasts. Selected cases that are poorly forecast and deemed important to wind power production will be re-simulated with modifications to key physical parameterizations (boundary layer, surface layer, etc.) in an attempt to reduce forecast errors. The most significant model improvements as well as the collective model improvements will further be tested in retrospective experiments involving the full RAP and HRRR domains in order to ensure robust improvements for general weather prediction as well as the complex flows of focus in this project. Retrospective runs will also be run by NOAA's hourly-updated North American Mesoscale Rapid Refresh (NAMRR) system, which includes the full 12-km North American domain and the 3-km CONUS nest domain.